Artificial Intelligence In Highway Location And Alignment Optimization Applications Of Genetic Algorithms In Searching Evaluating And Optimizing Highway Location And Alignments
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Artificial Intelligence In Highway Location And Alignment Optimization: Applications Of Genetic Algorithms In Searching, Evaluating, And Optimizing Highway Location And Alignments
This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location and alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A review of other promising optimization methods for the HAO problem is also provided in this monograph.
Applications of Evolutionary Computation
Author: Pablo García-Sánchez
language: en
Publisher: Springer Nature
Release Date: 2025-05-24
This two-volume set, LNCS 15612 and 15613 constitutes the refereed proceedings of the 28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025, in Trieste, Italy, during April 23–25, 2025, and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EuroGP. The 50 full papers and 18 short papers presented in this book were carefully reviewed and selected from 104 submissions. These papers have been organized in the following topical sections: Part I: EvoApplications. Part II: Evolutionary machine learning; 30 years of particle swarm optimisation; Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications; Bio-inspired Algorithms for Green Computing and Sustainable Complex Systems; Computational Intelligence for Sustainability; EvoLLMs (Integrating Evolutionary Computing with Large Language Models (LLMs); Evolutionary Computation in Edge, Fog, and Cloud Computing; Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition; Machine Learning and AI in Digital Healthcare and Personalized Medicine; Soft Computing Applied to Games.
Intelligent Road Design
Addressing the intelligent concepts of the ancient endeavour of road design, this book discusses how a road alignment optimization model can be developed and applied in real case studies. Based on research in intelligent road design and alignment optimization, it is suitable for road planners, designers, senior undergraduate and graduate students.